{"pk":29521,"title":"Active Word Learning through Self-supervision","subtitle":null,"abstract":"Models of cross-situational word learning typically character-ize the learner as a passive observer, but a language learn-ing child can actively participate in verbal and non-verbalcommunication. We present a computational study of cross-situational word learning to investigate whether a curious wordlearner who actively influences linguistic input in each contexthas an advantage over a passive learner. Our computationalmodel learns to map words to objects in real images by self-supervision through simulating both word comprehension andproduction. We examine different curiosity measures as guid-ing input selection, and analyze the relative impact of eachmethod. Our results suggest that active learning leads to higheroverall performance, and a formulation of curiosity which re-lies both on subjective novelty and plasticity yields the bestperformance and learning stability.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"Cross-situational word learning; Computationalmodelling; Active learning; Curiosity."}],"section":"Word Learning","is_remote":true,"remote_url":"https://escholarship.org/uc/item/2g84p0sk","frozenauthors":[{"first_name":"Lieke","middle_name":"","last_name":"Gelderloos","name_suffix":"","institution":"Tilburg University","department":""},{"first_name":"Alireza","middle_name":"Mahmoudi","last_name":"Kamelabad","name_suffix":"","institution":"University of Trento","department":""},{"first_name":"Afra","middle_name":"","last_name":"Alishahi","name_suffix":"","institution":"Tilburg University","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2020-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/29521/galley/19381/download/"}]}